Literature DB >> 18381945

Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma.

Hyun Goo Woo1, Eun Sung Park, Jae Hee Cheon, Ju Han Kim, Ju-Seog Lee, Bum Joon Park, Won Kim, Su Cheol Park, Young Jin Chung, Byeong Gwan Kim, Jung-Hwan Yoon, Hyo-Suk Lee, Chung Yong Kim, Nam-Joon Yi, Kyung-Suk Suh, Kuhn Uk Lee, In-Sun Chu, Tania Roskams, Snorri S Thorgeirsson, Yoon Jun Kim.   

Abstract

PURPOSE: The poor prognosis of hepatocellular carcinoma (HCC) is, in part, due to the high rate of recurrence even after "curative resection" of tumors. Therefore, it is axiomatic that the development of an effective prognostic prediction model for HCC recurrence after surgery would, at minimum, help to identify in advance those who would most benefit from the treatment, and at best, provide new therapeutic strategies for patients with a high risk of early recurrence. EXPERIMENTAL
DESIGN: For the prediction of the recurrence time in patients with HCC, gene expression profiles were generated in 65 HCC patients with hepatitis B infections. RESULT: Recurrence-associated gene expression signatures successfully discriminated between patients at high-risk and low-risk of early recurrence (P=1.9 x 10(-6), log-rank test). To test the consistency and robustness of the recurrence signature, we validated its prognostic power in an independent HCC microarray data set. CD24 was identified as a putative biomarker for the prediction of early recurrence. Genetic network analysis suggested that SP1 and peroxisome proliferator-activated receptor-alpha might have regulatory roles for the early recurrence of HCC.
CONCLUSION: We have identified a gene expression signature that effectively predicted early recurrence of HCC independent of microarray platforms and cohorts, and provided novel biological insights into the mechanisms of tumor recurrence.

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Year:  2008        PMID: 18381945     DOI: 10.1158/1078-0432.CCR-07-1473

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  66 in total

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